Identification of Potential Therapeutics to Conquer Drug Resistance in Salmonella typhimurium: Drug Repurposing Strategy

Flufenamic Acid, a Promising Agent for the Sensitization of Colistin-Resistant Gram-Negative Bacteria to Colistin

The continuous development of multidrug-resistant (MDR) Gram-negative bacteria poses a serious risk to public health on a worldwide scale. Colistin is used as the last-line antibiotic for the treatment of MDR pathogens, and colistin-resistant (COL-R) bacterial emergence thus has the potential to have a severe adverse impact on patient outcomes. In this study, synergistic activity was observed when colistin and flufenamic acid (FFA) were combined and used for the in vitro treatment of clinical COL-R Pseudomonas aeruginosa, Escherichia coli, Klebsiella pneumoniae, and Acinetobacter baumannii strains, as shown by checkerboard and time-kill assays. Crystal violet staining and scanning electron microscopy revealed the synergistic action of colistin-FFA against biofilms. When used to treat murine RAW264.7 macrophages, this combination did not induce any adverse toxicity. Strikingly, the survival rates of bacterially infected Galleria mellonella larvae were improved by such combination treatment, which was also sufficient to reduce the measured bacterial loads in a murine thigh infection model. Mechanistic propidium iodide (PI) staining analysis further demonstrated the ability of these agents to alter bacterial permeability in a manner that enhanced the efficacy of colistin treatment. Together, these data thus demonstrate that colistin and FFA can be synergistically combined to combat the spread of COL-R Gram-negative bacteria, providing a promising therapeutic tool with the potential to protect against COL-R bacterial infections and improve patient outcomes. IMPORTANCE Colistin is a last-line antibiotic used for the treatment of MDR Gram-negative bacterial infections. However, increasing resistance to it has been observed during clinical treatment. In this work, we assessed the efficacy of the combination of colistin and FFA for the treatment of COL-R bacterial isolates, demonstrating that the combined treatment has effective antibacterial and antibiofilm activities. Due to its low cytotoxicity and good therapeutic effects in vitro, the colistin-FFA combination may be a potential candidate for research into a resistance-modifying agent to combat infections caused by COL-R Gram-negative bacteria.

Antibacterial and antibiofilm effects of flufenamic acid against methicillin-resistant Staphylococcus aureus

Methicillin-resistant Staphylococcus aureus (MRSA) infections are one of the most serious surgery complications, and their prevention is of utmost importance. Flufenamic acid is a non-steroid anti-inflammatory drug approved for clinical use to relieve inflammation and pain in rheumatoid arthritis patients. In this study, we explored the antibacterial efficacy of flufenamic acid and the mechanisms underlying this effect. By using minimal inhibitory concentration (MIC), time-kill, resistance induction assays, and the antibiotic synergy test, we demonstrated that flufenamic acid inhibited the growth of methicillin-resistant staphylococci and did not induce resistance when it was used at the MIC. Furthermore, flufenamic acid acted synergistically with the beta-lactam antibiotic oxacillin and did not show significant toxicity toward mammalian cells. The biofilm inhibition assay revealed that flufenamic acid could prevent biofilm formation on medical implants and destroy the ultrastructure of the bacterial cell wall. RNA sequencing and quantitative RT-PCR indicated that flufenamic acid inhibited the expression of genes associated with peptidoglycan biosynthesis, beta-lactam resistance, quorum sensing, and biofilm formation. Furthermore, flufenamic acid efficiently ameliorated a local infection caused by MRSA in mice. In conclusion, flufenamic acid may be a potent therapeutic compound against MRSA infections and a promising candidate for antimicrobial coating of implants and surgical devices.

Drug Screening for Discovery of Broad-spectrum Agents for Soil-transmitted Nematodes

Soil-transmitted nematodes (STNs), namely hookworms, whipworms, and ascarids, are extremely common parasites, infecting 1-2 billion of the poorest people worldwide. Two benzimidazoles, albendazole and mebendazole, are currently used in STN mass drug administration, with many instances of low/reduced activity reported. New drugs against STNs are urgently needed. We tested various models for STN drug screening with the aim of identifying the most effective tactics for the discovery of potent, safe and broad-spectrum agents. We screened a 1280-compound library of approved drugs to completion against late larval/adult stages and egg/larval stages of both the human hookworm parasite Ancylostoma ceylanicum and the free-living nematode Caenorhabditis elegans, which is often used as a surrogate for STNs in screens. The quality of positives was further evaluated based on cheminformatics/data mining analyses and activity against evolutionarily distant Trichuris muris whipworm adults. From these data, two pairs of positives, sulconazole/econazole and pararosaniline/cetylpyridinium, predicted to target nematode CYP-450 and HSP-90 respectively, were prioritized for in vivo evaluation against A. ceylanicum infections in hamsters. One of these positives, pararosaniline, showed a significant impact on hookworm fecundity in vivo. Taken together, our results suggest that anthelmintic screening with A. ceylanicum larval stages is superior to C. elegans based on both reduced false negative rate and superior overall quality of actives. Our results also highlight two potentially important targets for the discovery of broad-spectrum human STN drugs.

Exploration of the Anti-Inflammatory Drug Space Through Network Pharmacology: Applications for Drug Repurposing

The quintessential biological response to disease is inflammation. It is a driver and an important element in a wide range of pathological states. Pharmacological management of inflammation is therefore central in the clinical setting. Anti-inflammatory drugs modulate specific molecules involved in the inflammatory response; these drugs are traditionally classified as steroidal and non-steroidal drugs. However, the effects of these drugs are rarely limited to their canonical targets, affecting other molecules and altering biological functions with system-wide effects that can lead to the emergence of secondary therapeutic applications or adverse drug reactions (ADRs). In this study, relationships among anti-inflammatory drugs, functional pathways, and ADRs were explored through network models. We integrated structural drug information, experimental anti-inflammatory drug perturbation gene expression profiles obtained from the Connectivity Map and Library of Integrated Network-Based Cellular Signatures, functional pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases, as well as adverse reaction information from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The network models comprise nodes representing anti-inflammatory drugs, functional pathways, and adverse effects. We identified structural and gene perturbation similarities linking anti-inflammatory drugs. Functional pathways were connected to drugs by implementing Gene Set Enrichment Analysis (GSEA). Drugs and adverse effects were connected based on the proportional reporting ratio (PRR) of an adverse effect in response to a given drug. Through these network models, relationships among anti-inflammatory drugs, their functional effects at the pathway level, and their adverse effects were explored. These networks comprise 70 different anti-inflammatory drugs, 462 functional pathways, and 1,175 ADRs. Network-based properties, such as degree, clustering coefficient, and node strength, were used to identify new therapeutic applications within and beyond the anti-inflammatory context, as well as ADR risk for these drugs, helping to select better repurposing candidates. Based on these parameters, we identified naproxen, meloxicam, etodolac, tenoxicam, flufenamic acid, fenoprofen, and nabumetone as candidates for drug repurposing with lower ADR risk. This network-based analysis pipeline provides a novel way to explore the effects of drugs in a therapeutic space.